{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_OEACZptdHC7"
   },
   "source": [
    "Please run those two cells before running the Notebook!\n",
    "\n",
    "As those plotting settings are standard throughout the book, we do not show them in the book every time we plot something."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T10:48:06.120195Z",
     "start_time": "2020-01-29T10:48:05.814125Z"
    },
    "id": "_JscbREmdHC-"
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = \"retina\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T10:48:13.141309Z",
     "start_time": "2020-01-29T10:48:13.137453Z"
    },
    "id": "r6OEEsWTdHDB"
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import warnings\n",
    "from pandas.core.common import SettingWithCopyWarning\n",
    "warnings.simplefilter(action=\"ignore\", category=FutureWarning)\n",
    "warnings.simplefilter(action=\"ignore\", category=SettingWithCopyWarning)\n",
    "\n",
    "# feel free to modify, for example, change the context to \"notebook\"\n",
    "sns.set_theme(context=\"talk\", style=\"whitegrid\", \n",
    "              palette=\"colorblind\", color_codes=True, \n",
    "              rc={\"figure.figsize\": [12, 8]})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nS3hr1kUdHDB"
   },
   "source": [
    "# Chapter 8 - Multi-Factor Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8.1 Estimating the CAPM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to do it..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Import the libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:04:31.496882Z",
     "start_time": "2020-01-25T20:04:29.060580Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import statsmodels.api as sm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Specify the risky asset, the benchmark, and the time horizon:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:04:31.508134Z",
     "start_time": "2020-01-25T20:04:31.505324Z"
    }
   },
   "outputs": [],
   "source": [
    "RISKY_ASSET = \"AMZN\"\n",
    "MARKET_BENCHMARK = \"^GSPC\"\n",
    "START_DATE = \"2016-01-01\"\n",
    "END_DATE = \"2020-12-31\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Download data from Yahoo Finance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:04:31.755119Z",
     "start_time": "2020-01-25T20:04:31.516384Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloaded 1259 rows of data.\n"
     ]
    }
   ],
   "source": [
    "df = yf.download([RISKY_ASSET, MARKET_BENCHMARK],\n",
    "                 start=START_DATE,\n",
    "                 end=END_DATE,\n",
    "                 adjusted=True,\n",
    "                 progress=False)\n",
    "\n",
    "print(f'Downloaded {df.shape[0]} rows of data.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Resample to monthly data and calculate simple returns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:04:53.657590Z",
     "start_time": "2020-01-25T20:04:53.620402Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>asset</th>\n",
       "      <th>market</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-31</th>\n",
       "      <td>-0.131515</td>\n",
       "      <td>-0.050735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-29</th>\n",
       "      <td>-0.058739</td>\n",
       "      <td>-0.004128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-31</th>\n",
       "      <td>0.074423</td>\n",
       "      <td>0.065991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04-30</th>\n",
       "      <td>0.111094</td>\n",
       "      <td>0.002699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-31</th>\n",
       "      <td>0.095817</td>\n",
       "      <td>0.015325</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               asset    market\n",
       "Date                          \n",
       "2016-01-31 -0.131515 -0.050735\n",
       "2016-02-29 -0.058739 -0.004128\n",
       "2016-03-31  0.074423  0.065991\n",
       "2016-04-30  0.111094  0.002699\n",
       "2016-05-31  0.095817  0.015325"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = (\n",
    "    df[\"Adj Close\"]\n",
    "    .rename(columns={RISKY_ASSET: \"asset\", \n",
    "                     MARKET_BENCHMARK: \"market\"})\n",
    "    .resample(\"M\")\n",
    "    .last()\n",
    "    .pct_change()\n",
    "    .dropna()\n",
    ")\n",
    "X.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-17T21:29:46.889870Z",
     "start_time": "2019-07-17T21:29:46.886160Z"
    }
   },
   "source": [
    "5. Calculate beta using the covariance approach: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-19T19:54:06.705710Z",
     "start_time": "2020-01-19T19:54:06.699353Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.2034611811489746"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covariance = X.cov().iloc[0,1]\n",
    "benchmark_variance = X.market.var()\n",
    "beta = covariance / benchmark_variance\n",
    "beta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6. Prepare the input and estimate CAPM as a linear regression:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-19T19:54:09.193249Z",
     "start_time": "2020-01-19T19:54:09.170750Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                  asset   R-squared:                       0.408\n",
      "Model:                            OLS   Adj. R-squared:                  0.398\n",
      "Method:                 Least Squares   F-statistic:                     40.05\n",
      "Date:                Fri, 22 Jul 2022   Prob (F-statistic):           3.89e-08\n",
      "Time:                        00:19:10   Log-Likelihood:                 80.639\n",
      "No. Observations:                  60   AIC:                            -157.3\n",
      "Df Residuals:                      58   BIC:                            -153.1\n",
      "Df Model:                           1                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const          0.0167      0.009      1.953      0.056      -0.000       0.034\n",
      "market         1.2035      0.190      6.329      0.000       0.823       1.584\n",
      "==============================================================================\n",
      "Omnibus:                        2.202   Durbin-Watson:                   1.783\n",
      "Prob(Omnibus):                  0.333   Jarque-Bera (JB):                1.814\n",
      "Skew:                           0.426   Prob(JB):                        0.404\n",
      "Kurtosis:                       2.989   Cond. No.                         23.0\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "# separate target\n",
    "y = X.pop(\"asset\")\n",
    "\n",
    "# add constant\n",
    "X = sm.add_constant(X)\n",
    "\n",
    "# define and fit the regression model \n",
    "capm_model = sm.OLS(y, X).fit()\n",
    "\n",
    "# print results \n",
    "print(capm_model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or, using the formula notation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                  asset   R-squared:                       0.408\n",
      "Model:                            OLS   Adj. R-squared:                  0.398\n",
      "Method:                 Least Squares   F-statistic:                     40.05\n",
      "Date:                Wed, 02 Mar 2022   Prob (F-statistic):           3.89e-08\n",
      "Time:                        23:28:12   Log-Likelihood:                 80.639\n",
      "No. Observations:                  60   AIC:                            -157.3\n",
      "Df Residuals:                      58   BIC:                            -153.1\n",
      "Df Model:                           1                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      0.0167      0.009      1.953      0.056      -0.000       0.034\n",
      "market         1.2035      0.190      6.329      0.000       0.823       1.584\n",
      "==============================================================================\n",
      "Omnibus:                        2.202   Durbin-Watson:                   1.783\n",
      "Prob(Omnibus):                  0.333   Jarque-Bera (JB):                1.814\n",
      "Skew:                           0.426   Prob(JB):                        0.404\n",
      "Kurtosis:                       2.989   Cond. No.                         23.0\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "import statsmodels.formula.api as smf\n",
    "\n",
    "# rerun step 4 to have a DF with columns: `asset` and `market`\n",
    "X = df[\"Adj Close\"].rename(columns={RISKY_ASSET: \"asset\", \n",
    "                                    MARKET_BENCHMARK: \"market\"}) \\\n",
    "                   .resample(\"M\") \\\n",
    "                   .last() \\\n",
    "                   .pct_change() \\\n",
    "                   .dropna()\n",
    "\n",
    "# define and fit the regression model \n",
    "capm_model = smf.ols(formula=\"asset ~ market\", data=X).fit()\n",
    "\n",
    "# print results \n",
    "print(capm_model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### There's more"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Risk-free rate (13 Week Treasury Bill)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:30:02.795490Z",
     "start_time": "2020-01-25T20:29:57.736730Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 549,
       "width": 839
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# period length in days\n",
    "N_DAYS = 90\n",
    "\n",
    "# download data from Yahoo finance\n",
    "df_rf = yf.download(\"^IRX\",\n",
    "                    start=START_DATE,\n",
    "                    end=END_DATE,\n",
    "                    progress=False)\n",
    "\n",
    "# resample to monthly by taking last value from each month\n",
    "rf = df_rf.resample(\"M\").last().Close / 100\n",
    "\n",
    "# calculate the corresponding daily risk-free return  \n",
    "rf = ( 1 / (1 - rf * N_DAYS / 360) )**(1 / N_DAYS)  \n",
    "\n",
    "# convert to monthly and subtract 1\n",
    "rf = (rf ** 30) - 1 \n",
    "\n",
    "# plot the risk-free rate\n",
    "rf.plot(title=\"Risk-free rate (13 Week Treasury Bill)\")\n",
    "\n",
    "sns.despine()\n",
    "plt.tight_layout()\n",
    "# plt.savefig(\"images/figure_9_2\", dpi=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Risk-free rate (3-Month Treasury Bill)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:30:19.688513Z",
     "start_time": "2020-01-25T20:30:13.722057Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 549,
       "width": 839
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas_datareader.data as web\n",
    "\n",
    "# download the data \n",
    "rf = web.DataReader(\n",
    "    \"TB3MS\", \"fred\", start=START_DATE, end=END_DATE\n",
    ")\n",
    "\n",
    "# convert to monthly\n",
    "rf = (1 + (rf / 100)) ** (1 / 12) - 1\n",
    "\n",
    "# plot the risk-free rate\n",
    "rf.plot(title=\"Risk-free rate (3-Month Treasury Bill)\")\n",
    "\n",
    "sns.despine()\n",
    "plt.tight_layout()\n",
    "# plt.savefig(\"images/figure_9_3\", dpi=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8.2 Estimating the Fama-French three-factor model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to do it..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Import the libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:45:47.696443Z",
     "start_time": "2020-01-25T20:45:47.693642Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import statsmodels.formula.api as smf\n",
    "import pandas_datareader.data as web"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Define parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "RISKY_ASSET = \"AAPL\"\n",
    "START_DATE = \"2016-01-01\"\n",
    "END_DATE = \"2020-12-31\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Download the dataset containing the risk factors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T21:00:16.771198Z",
     "start_time": "2020-01-25T21:00:16.468270Z"
    }
   },
   "outputs": [],
   "source": [
    "ff_dict = web.DataReader(\"F-F_Research_Data_Factors\", \n",
    "                         \"famafrench\", \n",
    "                         start=START_DATE,\n",
    "                         end=END_DATE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T21:00:16.826373Z",
     "start_time": "2020-01-25T21:00:16.822776Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys([0, 1, 'DESCR'])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ff_dict.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T21:00:16.887440Z",
     "start_time": "2020-01-25T21:00:16.882970Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F-F Research Data Factors\n",
      "-------------------------\n",
      "\n",
      "This file was created by CMPT_ME_BEME_RETS using the 202201 CRSP database. The 1-month TBill return is from Ibbotson and Associates, Inc. Copyright 2022 Kenneth R. French\n",
      "\n",
      "  0 : (60 rows x 4 cols)\n",
      "  1 : Annual Factors: January-December (5 rows x 4 cols)\n"
     ]
    }
   ],
   "source": [
    "print(ff_dict['DESCR'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Select the appropriate dataset and divide the values by 100:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MKT</th>\n",
       "      <th>SMB</th>\n",
       "      <th>HML</th>\n",
       "      <th>RF</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01</th>\n",
       "      <td>-0.0577</td>\n",
       "      <td>-0.0339</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02</th>\n",
       "      <td>-0.0008</td>\n",
       "      <td>0.0081</td>\n",
       "      <td>-0.0057</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03</th>\n",
       "      <td>0.0696</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04</th>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0067</td>\n",
       "      <td>0.0321</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05</th>\n",
       "      <td>0.0178</td>\n",
       "      <td>-0.0019</td>\n",
       "      <td>-0.0165</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            MKT     SMB     HML      RF\n",
       "Date                                   \n",
       "2016-01 -0.0577 -0.0339  0.0207  0.0001\n",
       "2016-02 -0.0008  0.0081 -0.0057  0.0002\n",
       "2016-03  0.0696  0.0075  0.0110  0.0002\n",
       "2016-04  0.0092  0.0067  0.0321  0.0001\n",
       "2016-05  0.0178 -0.0019 -0.0165  0.0001"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factor_3_df = ff_dict[0].rename(columns={\"Mkt-RF\": \"MKT\"}) \\\n",
    "                        .div(100)\n",
    "\n",
    "factor_3_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. Download the prices of the risky asset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:48:48.281828Z",
     "start_time": "2020-01-25T20:48:48.103450Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloaded 1259 rows of data.\n"
     ]
    }
   ],
   "source": [
    "asset_df = yf.download(RISKY_ASSET,\n",
    "                       start=START_DATE,\n",
    "                       end=END_DATE,\n",
    "                       adjusted=True,\n",
    "                       progress=False)\n",
    "\n",
    "print(f\"Downloaded {asset_df.shape[0]} rows of data.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-05T18:30:40.781647Z",
     "start_time": "2019-07-05T18:30:40.778104Z"
    }
   },
   "source": [
    "6. Calculate monthly returns on the risky asset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:48:51.665914Z",
     "start_time": "2020-01-25T20:48:51.651938Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2016-01   -0.075242\n",
       "2016-02   -0.001288\n",
       "2016-03    0.127211\n",
       "2016-04   -0.139921\n",
       "2016-05    0.071773\n",
       "Freq: M, Name: rtn, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = asset_df[\"Adj Close\"].resample(\"M\") \\\n",
    "                         .last() \\\n",
    "                         .pct_change() \\\n",
    "                         .dropna()\n",
    "\n",
    "y.index = y.index.to_period(\"m\")\n",
    "y.name = \"rtn\"\n",
    "y.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7. Merge the datasets and calculate excess returns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:50:09.167046Z",
     "start_time": "2020-01-25T20:50:09.162415Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MKT</th>\n",
       "      <th>SMB</th>\n",
       "      <th>HML</th>\n",
       "      <th>RF</th>\n",
       "      <th>rtn</th>\n",
       "      <th>excess_rtn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01</th>\n",
       "      <td>-0.0577</td>\n",
       "      <td>-0.0339</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>-0.075242</td>\n",
       "      <td>-0.075342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02</th>\n",
       "      <td>-0.0008</td>\n",
       "      <td>0.0081</td>\n",
       "      <td>-0.0057</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>-0.001288</td>\n",
       "      <td>-0.001488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03</th>\n",
       "      <td>0.0696</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>0.127211</td>\n",
       "      <td>0.127011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04</th>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0067</td>\n",
       "      <td>0.0321</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>-0.139921</td>\n",
       "      <td>-0.140021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05</th>\n",
       "      <td>0.0178</td>\n",
       "      <td>-0.0019</td>\n",
       "      <td>-0.0165</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.071773</td>\n",
       "      <td>0.071673</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            MKT     SMB     HML      RF       rtn  excess_rtn\n",
       "Date                                                         \n",
       "2016-01 -0.0577 -0.0339  0.0207  0.0001 -0.075242   -0.075342\n",
       "2016-02 -0.0008  0.0081 -0.0057  0.0002 -0.001288   -0.001488\n",
       "2016-03  0.0696  0.0075  0.0110  0.0002  0.127211    0.127011\n",
       "2016-04  0.0092  0.0067  0.0321  0.0001 -0.139921   -0.140021\n",
       "2016-05  0.0178 -0.0019 -0.0165  0.0001  0.071773    0.071673"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factor_3_df = factor_3_df.join(y)\n",
    "factor_3_df[\"excess_rtn\"] = (\n",
    "    factor_3_df[\"rtn\"] - factor_3_df[\"RF\"]\n",
    ")\n",
    "factor_3_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "8. Estimate the three-factor model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:50:09.789755Z",
     "start_time": "2020-01-25T20:50:09.762734Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:             excess_rtn   R-squared:                       0.504\n",
      "Model:                            OLS   Adj. R-squared:                  0.477\n",
      "Method:                 Least Squares   F-statistic:                     18.94\n",
      "Date:                Wed, 02 Mar 2022   Prob (F-statistic):           1.32e-08\n",
      "Time:                        23:48:12   Log-Likelihood:                 82.679\n",
      "No. Observations:                  60   AIC:                            -157.4\n",
      "Df Residuals:                      56   BIC:                            -149.0\n",
      "Df Model:                           3                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      0.0084      0.009      0.954      0.344      -0.009       0.026\n",
      "MKT            1.4264      0.198      7.213      0.000       1.030       1.823\n",
      "SMB           -0.4590      0.359     -1.280      0.206      -1.177       0.259\n",
      "HML           -0.7186      0.260     -2.759      0.008      -1.240      -0.197\n",
      "==============================================================================\n",
      "Omnibus:                        8.642   Durbin-Watson:                   2.458\n",
      "Prob(Omnibus):                  0.013   Jarque-Bera (JB):                8.952\n",
      "Skew:                          -0.652   Prob(JB):                       0.0114\n",
      "Kurtosis:                       4.371   Cond. No.                         45.8\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "# define and fit the regression model \n",
    "ff_model = smf.ols(formula=\"excess_rtn ~ MKT + SMB + HML\", \n",
    "                   data=factor_3_df).fit()\n",
    "\n",
    "# print results \n",
    "print(ff_model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### There's more"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print available datasets (here only first 5):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T21:00:16.415253Z",
     "start_time": "2020-01-25T21:00:14.609501Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['F-F_Research_Data_Factors',\n",
       " 'F-F_Research_Data_Factors_weekly',\n",
       " 'F-F_Research_Data_Factors_daily',\n",
       " 'F-F_Research_Data_5_Factors_2x3',\n",
       " 'F-F_Research_Data_5_Factors_2x3_daily']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas_datareader.famafrench import get_available_datasets\n",
    "\n",
    "get_available_datasets()[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bonus"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Download data from prof. French's website:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To do so, we used the fact that we can execute bash commands in Jupyter Notebooks by preceding them with `!`. First, we downloaded the file using wget and then unzipped it using unzip. There are also ways to do this in Python only, but this seemed like a good place to introduce the possibility of mixing up bash script into the Notebooks. The link to the monthly data is always the same, and the file is updated every month. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-19T19:59:26.513650Z",
     "start_time": "2020-01-19T19:59:24.755998Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "zsh:1: command not found: wget\n",
      "unzip:  cannot find or open F-F_Research_Data_Factors_CSV.zip, F-F_Research_Data_Factors_CSV.zip.zip or F-F_Research_Data_Factors_CSV.zip.ZIP.\n",
      "rm: F-F_Research_Data_Factors_CSV.zip: No such file or directory\n"
     ]
    }
   ],
   "source": [
    "# download the zip file from Prof. French's website\n",
    "!wget http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/F-F_Research_Data_Factors_CSV.zip\n",
    "\n",
    "# unpack the zip file\n",
    "!unzip -a F-F_Research_Data_Factors_CSV.zip\n",
    "\n",
    "# remove the zip file\n",
    "!rm F-F_Research_Data_Factors_CSV.zip"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Load data from the source CSV file and keep only the monthly data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:47:40.410667Z",
     "start_time": "2020-01-25T20:47:40.400397Z"
    }
   },
   "outputs": [],
   "source": [
    "# load data from CSV\n",
    "factor_3_df = pd.read_csv(\"F-F_Research_Data_Factors.csv\", skiprows=3)\n",
    "\n",
    "# identify where the annual data starts\n",
    "STR_TO_MATCH = \" Annual Factors: January-December \"\n",
    "indices = factor_3_df.iloc[:, 0] == STR_TO_MATCH\n",
    "start_of_annual = factor_3_df[indices].index[0]\n",
    "\n",
    "# keep only monthly data\n",
    "factor_3_df = factor_3_df[factor_3_df.index < start_of_annual]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Rename columns of the DataFrame, set a datetime index and filter by dates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T20:47:41.016860Z",
     "start_time": "2020-01-25T20:47:41.001267Z"
    }
   },
   "outputs": [],
   "source": [
    "# rename columns\n",
    "factor_3_df.columns = [\"date\", \"mkt\", \"smb\", \"hml\", \"rf\"]\n",
    "\n",
    "# convert strings to datetime\n",
    "factor_3_df[\"date\"] = (\n",
    "    pd.to_datetime(factor_3_df[\"date\"], format=\"%Y%m\")\n",
    "    .dt.strftime(\"%Y-%m\")\n",
    ")\n",
    "\n",
    "# set index\n",
    "factor_3_df = factor_3_df.set_index(\"date\")\n",
    "\n",
    "# filter only required dates\n",
    "factor_3_df = factor_3_df.loc[START_DATE:END_DATE]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Convert the values to numeric and divide by 100:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mkt</th>\n",
       "      <th>smb</th>\n",
       "      <th>hml</th>\n",
       "      <th>rf</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-02</th>\n",
       "      <td>-0.0007</td>\n",
       "      <td>0.0079</td>\n",
       "      <td>-0.0050</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03</th>\n",
       "      <td>0.0696</td>\n",
       "      <td>0.0087</td>\n",
       "      <td>0.0116</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04</th>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0069</td>\n",
       "      <td>0.0326</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05</th>\n",
       "      <td>0.0178</td>\n",
       "      <td>-0.0027</td>\n",
       "      <td>-0.0181</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06</th>\n",
       "      <td>-0.0005</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>-0.0147</td>\n",
       "      <td>0.0002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            mkt     smb     hml      rf\n",
       "date                                   \n",
       "2016-02 -0.0007  0.0079 -0.0050  0.0002\n",
       "2016-03  0.0696  0.0087  0.0116  0.0002\n",
       "2016-04  0.0092  0.0069  0.0326  0.0001\n",
       "2016-05  0.0178 -0.0027 -0.0181  0.0001\n",
       "2016-06 -0.0005  0.0065 -0.0147  0.0002"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factor_3_df = factor_3_df.apply(pd.to_numeric, \n",
    "                            errors=\"coerce\") \\\n",
    "                     .div(100)\n",
    "factor_3_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8.3 Estimating the rolling three-factor model on a portfolio of assets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to do it..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Import the libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T09:44:07.710284Z",
     "start_time": "2020-01-29T09:44:06.217752Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import yfinance as yf\n",
    "import statsmodels.formula.api as smf\n",
    "import pandas_datareader.data as web"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Define the parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T09:44:07.721786Z",
     "start_time": "2020-01-29T09:44:07.718682Z"
    }
   },
   "outputs": [],
   "source": [
    "ASSETS = [\"AMZN\", \"GOOG\", \"AAPL\", \"MSFT\"]\n",
    "WEIGHTS = [0.25, 0.25, 0.25, 0.25]\n",
    "START_DATE = \"2010-01-01\"\n",
    "END_DATE = \"2020-12-31\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Download the factor related data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T09:44:08.624754Z",
     "start_time": "2020-01-29T09:44:08.285860Z"
    }
   },
   "outputs": [],
   "source": [
    "factor_3_df = web.DataReader(\"F-F_Research_Data_Factors\", \n",
    "                             \"famafrench\", \n",
    "                             start=START_DATE,\n",
    "                             end=END_DATE)[0]\n",
    "factor_3_df = factor_3_df.div(100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Download the prices of risky assets from Yahoo Finance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T09:44:09.289538Z",
     "start_time": "2020-01-29T09:44:08.939559Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloaded 2769 rows of data.\n"
     ]
    }
   ],
   "source": [
    "asset_df = yf.download(ASSETS,\n",
    "                       start=START_DATE,\n",
    "                       end=END_DATE,\n",
    "                       adjusted=True,\n",
    "                       progress=False)\n",
    "\n",
    "print(f\"Downloaded {asset_df.shape[0]} rows of data.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. Calculate the monthly returns on the risky assets:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T09:44:10.079311Z",
     "start_time": "2020-01-29T09:44:10.052389Z"
    }
   },
   "outputs": [],
   "source": [
    "asset_df = asset_df[\"Adj Close\"].resample(\"M\") \\\n",
    "                                .last() \\\n",
    "                                .pct_change() \\\n",
    "                                .dropna()\n",
    "# reformat index for joining\n",
    "asset_df.index = asset_df.index.to_period(\"m\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6. Calculate the portfolio returns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T09:44:11.116482Z",
     "start_time": "2020-01-29T09:44:11.095431Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>portfolio_returns</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01</th>\n",
       "      <td>-0.088597</td>\n",
       "      <td>-0.067722</td>\n",
       "      <td>-0.145231</td>\n",
       "      <td>-0.075459</td>\n",
       "      <td>-0.094252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02</th>\n",
       "      <td>0.065396</td>\n",
       "      <td>-0.055897</td>\n",
       "      <td>-0.005925</td>\n",
       "      <td>0.022146</td>\n",
       "      <td>0.006430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-03</th>\n",
       "      <td>0.148470</td>\n",
       "      <td>0.146706</td>\n",
       "      <td>0.076538</td>\n",
       "      <td>0.021626</td>\n",
       "      <td>0.098335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04</th>\n",
       "      <td>0.111022</td>\n",
       "      <td>0.009796</td>\n",
       "      <td>-0.073036</td>\n",
       "      <td>0.042677</td>\n",
       "      <td>0.022615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-05</th>\n",
       "      <td>-0.016125</td>\n",
       "      <td>-0.084902</td>\n",
       "      <td>-0.076222</td>\n",
       "      <td>-0.151395</td>\n",
       "      <td>-0.082161</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             AAPL      AMZN      GOOG      MSFT  portfolio_returns\n",
       "Date                                                              \n",
       "2010-01 -0.088597 -0.067722 -0.145231 -0.075459          -0.094252\n",
       "2010-02  0.065396 -0.055897 -0.005925  0.022146           0.006430\n",
       "2010-03  0.148470  0.146706  0.076538  0.021626           0.098335\n",
       "2010-04  0.111022  0.009796 -0.073036  0.042677           0.022615\n",
       "2010-05 -0.016125 -0.084902 -0.076222 -0.151395          -0.082161"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "asset_df[\"portfolio_returns\"] = np.matmul(\n",
    "    asset_df[ASSETS].values, \n",
    "    WEIGHTS\n",
    ")\n",
    "asset_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T09:44:31.735019Z",
     "start_time": "2020-01-29T09:44:27.830125Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 497,
       "width": 729
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "asset_df.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-27T20:33:39.379864Z",
     "start_time": "2019-07-27T20:33:39.376122Z"
    }
   },
   "source": [
    "7. Merge the datasets:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T09:44:35.683287Z",
     "start_time": "2020-01-29T09:44:35.676407Z"
    }
   },
   "outputs": [],
   "source": [
    "factor_3_df = asset_df.join(factor_3_df).drop(ASSETS, axis=1)\n",
    "factor_3_df.columns = [\"portf_rtn\", \"mkt\", \"smb\", \"hml\", \"rf\"]\n",
    "factor_3_df[\"portf_ex_rtn\"] = (\n",
    "    factor_3_df[\"portf_rtn\"] - factor_3_df[\"rf\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-27T20:33:41.550073Z",
     "start_time": "2019-07-27T20:33:41.546557Z"
    }
   },
   "source": [
    "8. Define a function for the rolling n-factor model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T10:02:23.597243Z",
     "start_time": "2020-01-29T10:02:23.592062Z"
    }
   },
   "outputs": [],
   "source": [
    "def rolling_factor_model(input_data, formula, window_size):\n",
    "    \"\"\"\n",
    "    Function for estimating the Fama-French (n-factor) model using a rolling window of fixed size.\n",
    "    \n",
    "    Parameters\n",
    "    ------------\n",
    "    input_data : pd.DataFrame\n",
    "        A DataFrame containing the factors and asset/portfolio returns\n",
    "    formula : str\n",
    "        `statsmodels` compatible formula representing the OLS regression  \n",
    "    window_size : int\n",
    "        Rolling window length.\n",
    "    \n",
    "    Returns\n",
    "    -----------\n",
    "    coeffs_df : pd.DataFrame\n",
    "        DataFrame containing the intercept and the three factors for each iteration.\n",
    "    \"\"\"\n",
    "\n",
    "    coeffs = []\n",
    "\n",
    "    for start_ind in range(len(input_data) - window_size + 1):        \n",
    "        end_ind = start_ind + window_size\n",
    "\n",
    "        # define and fit the regression model \n",
    "        ff_model = smf.ols(\n",
    "            formula=formula, \n",
    "            data=input_data[start_ind:end_ind]\n",
    "        ).fit()\n",
    "   \n",
    "        # store coefficients\n",
    "        coeffs.append(ff_model.params)\n",
    "    \n",
    "    coeffs_df = pd.DataFrame(\n",
    "        coeffs, \n",
    "        index=input_data.index[window_size - 1:]\n",
    "    )\n",
    "\n",
    "    return coeffs_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "9. Estimate the rolling three-factor model and plot the results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-29T10:02:30.494210Z",
     "start_time": "2020-01-29T10:02:25.939840Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 549,
       "width": 839
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "MODEL_FORMULA = \"portf_ex_rtn ~ mkt + smb + hml\"\n",
    "results_df = rolling_factor_model(factor_3_df, \n",
    "                                  MODEL_FORMULA, \n",
    "                                  window_size=60)\n",
    "(\n",
    "    results_df\n",
    "    .plot(title = \"Rolling Fama-French Three-Factor model\",\n",
    "          style=[\"-\", \"--\", \"-.\", \":\"])\n",
    "    .legend(loc=\"center left\",bbox_to_anchor=(1.0, 0.5))\n",
    ")\n",
    "\n",
    "sns.despine()\n",
    "plt.tight_layout()\n",
    "# plt.savefig(\"images/figure_9_6\", dpi=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8.4 Estimating the four- and five-factor models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to do it..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Import the libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T21:32:59.744013Z",
     "start_time": "2020-01-25T21:32:59.121212Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import statsmodels.formula.api as smf\n",
    "import pandas_datareader.data as web"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-30T21:13:07.117897Z",
     "start_time": "2019-07-30T21:13:07.113317Z"
    }
   },
   "source": [
    "2. Specify the risky asset and the time horizon:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T21:32:59.882469Z",
     "start_time": "2020-01-25T21:32:59.880245Z"
    }
   },
   "outputs": [],
   "source": [
    "RISKY_ASSET = \"AMZN\"\n",
    "START_DATE = \"2016-01-01\"\n",
    "END_DATE = \"2020-12-31\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Download the risk factors from prof. French's website:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T21:37:47.321394Z",
     "start_time": "2020-01-25T21:37:46.722478Z"
    }
   },
   "outputs": [],
   "source": [
    "# three factors \n",
    "factor_3_df = web.DataReader(\"F-F_Research_Data_Factors\", \n",
    "                             \"famafrench\", \n",
    "                             start=START_DATE,\n",
    "                             end=END_DATE)[0]\n",
    "\n",
    "# momentum factor\n",
    "momentum_df = web.DataReader(\"F-F_Momentum_Factor\", \n",
    "                             \"famafrench\", \n",
    "                             start=START_DATE,\n",
    "                             end=END_DATE)[0]\n",
    "      \n",
    "# five factors\n",
    "factor_5_df = web.DataReader(\"F-F_Research_Data_5_Factors_2x3\", \n",
    "                             \"famafrench\", \n",
    "                             start=START_DATE,\n",
    "                             end=END_DATE)[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Download the data of the risky asset from Yahoo Finance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-25T21:32:45.021706Z",
     "start_time": "2020-01-25T21:32:44.855063Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloaded 1259 rows of data.\n"
     ]
    }
   ],
   "source": [
    "asset_df = yf.download(RISKY_ASSET,\n",
    "                       start=START_DATE,\n",
    "                       end=END_DATE,\n",
    "                       adjusted=True,\n",
    "                       progress=False)\n",
    "\n",
    "print(f\"Downloaded {asset_df.shape[0]} rows of data.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-30T21:13:14.206767Z",
     "start_time": "2019-07-30T21:13:14.203304Z"
    }
   },
   "source": [
    "5. Calculate monthly returns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-19T20:31:09.165863Z",
     "start_time": "2020-01-19T20:31:09.154418Z"
    }
   },
   "outputs": [],
   "source": [
    "y = asset_df[\"Adj Close\"].resample(\"M\") \\\n",
    "                         .last() \\\n",
    "                         .pct_change() \\\n",
    "                         .dropna()\n",
    "\n",
    "y.index = y.index.to_period(\"m\")\n",
    "y.name = \"rtn\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6. Merge the datasets for the four-factor models:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-19T20:31:11.312066Z",
     "start_time": "2020-01-19T20:31:11.289272Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mkt</th>\n",
       "      <th>smb</th>\n",
       "      <th>hml</th>\n",
       "      <th>rf</th>\n",
       "      <th>mom</th>\n",
       "      <th>rtn</th>\n",
       "      <th>excess_rtn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01</th>\n",
       "      <td>-0.0577</td>\n",
       "      <td>-0.0339</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0139</td>\n",
       "      <td>-0.131516</td>\n",
       "      <td>-0.131616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02</th>\n",
       "      <td>-0.0008</td>\n",
       "      <td>0.0081</td>\n",
       "      <td>-0.0057</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>-0.0426</td>\n",
       "      <td>-0.058739</td>\n",
       "      <td>-0.058939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03</th>\n",
       "      <td>0.0696</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>-0.0504</td>\n",
       "      <td>0.074423</td>\n",
       "      <td>0.074223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04</th>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0067</td>\n",
       "      <td>0.0321</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>-0.0607</td>\n",
       "      <td>0.111094</td>\n",
       "      <td>0.110994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05</th>\n",
       "      <td>0.0178</td>\n",
       "      <td>-0.0019</td>\n",
       "      <td>-0.0165</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0137</td>\n",
       "      <td>0.095817</td>\n",
       "      <td>0.095717</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            mkt     smb     hml      rf     mom       rtn  excess_rtn\n",
       "Date                                                                 \n",
       "2016-01 -0.0577 -0.0339  0.0207  0.0001  0.0139 -0.131516   -0.131616\n",
       "2016-02 -0.0008  0.0081 -0.0057  0.0002 -0.0426 -0.058739   -0.058939\n",
       "2016-03  0.0696  0.0075  0.0110  0.0002 -0.0504  0.074423    0.074223\n",
       "2016-04  0.0092  0.0067  0.0321  0.0001 -0.0607  0.111094    0.110994\n",
       "2016-05  0.0178 -0.0019 -0.0165  0.0001  0.0137  0.095817    0.095717"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# join all datasets on the index\n",
    "factor_4_df = factor_3_df.join(momentum_df).join(y)\n",
    "\n",
    "# rename columns\n",
    "factor_4_df.columns = [\"mkt\", \"smb\", \"hml\", \"rf\", \"mom\", \"rtn\"]\n",
    "\n",
    "# divide everything (except returns) by 100\n",
    "factor_4_df.loc[:, factor_4_df.columns != \"rtn\"] /= 100\n",
    "\n",
    "# calculate excess returns\n",
    "factor_4_df[\"excess_rtn\"] = (\n",
    "    factor_4_df[\"rtn\"] - factor_4_df[\"rf\"]\n",
    ")\n",
    "\n",
    "factor_4_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7. Merge the datasets for the five-factor models:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-19T20:31:14.376169Z",
     "start_time": "2020-01-19T20:31:14.353016Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mkt</th>\n",
       "      <th>smb</th>\n",
       "      <th>hml</th>\n",
       "      <th>rmw</th>\n",
       "      <th>cma</th>\n",
       "      <th>rf</th>\n",
       "      <th>rtn</th>\n",
       "      <th>excess_rtn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01</th>\n",
       "      <td>-0.0577</td>\n",
       "      <td>-0.0342</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0281</td>\n",
       "      <td>0.0309</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>-0.131516</td>\n",
       "      <td>-0.131616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02</th>\n",
       "      <td>-0.0008</td>\n",
       "      <td>0.0093</td>\n",
       "      <td>-0.0057</td>\n",
       "      <td>0.0332</td>\n",
       "      <td>0.0196</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>-0.058739</td>\n",
       "      <td>-0.058939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03</th>\n",
       "      <td>0.0696</td>\n",
       "      <td>0.0101</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>0.074423</td>\n",
       "      <td>0.074223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04</th>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0115</td>\n",
       "      <td>0.0321</td>\n",
       "      <td>-0.0292</td>\n",
       "      <td>0.0189</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.111094</td>\n",
       "      <td>0.110994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05</th>\n",
       "      <td>0.0178</td>\n",
       "      <td>-0.0064</td>\n",
       "      <td>-0.0165</td>\n",
       "      <td>-0.0109</td>\n",
       "      <td>-0.0249</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.095817</td>\n",
       "      <td>0.095717</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            mkt     smb     hml     rmw     cma      rf       rtn  excess_rtn\n",
       "Date                                                                         \n",
       "2016-01 -0.0577 -0.0342  0.0207  0.0281  0.0309  0.0001 -0.131516   -0.131616\n",
       "2016-02 -0.0008  0.0093 -0.0057  0.0332  0.0196  0.0002 -0.058739   -0.058939\n",
       "2016-03  0.0696  0.0101  0.0110  0.0073 -0.0002  0.0002  0.074423    0.074223\n",
       "2016-04  0.0092  0.0115  0.0321 -0.0292  0.0189  0.0001  0.111094    0.110994\n",
       "2016-05  0.0178 -0.0064 -0.0165 -0.0109 -0.0249  0.0001  0.095817    0.095717"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# join all datasets on the index\n",
    "factor_5_df = factor_5_df.join(y)\n",
    "\n",
    "# rename columns\n",
    "factor_5_df.columns = [\n",
    "    \"mkt\", \"smb\", \"hml\", \"rmw\", \"cma\", \"rf\", \"rtn\"\n",
    "]\n",
    "\n",
    "# divide everything (except returns) by 100\n",
    "factor_5_df.loc[:, factor_5_df.columns != \"rtn\"] /= 100\n",
    "\n",
    "# calculate excess returns\n",
    "factor_5_df[\"excess_rtn\"] = (\n",
    "    factor_5_df[\"rtn\"] - factor_5_df[\"rf\"]\n",
    ")\n",
    "\n",
    "factor_5_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "8. Estimate the four-factor model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-19T20:31:16.823818Z",
     "start_time": "2020-01-19T20:31:16.795323Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:             excess_rtn   R-squared:                       0.563\n",
      "Model:                            OLS   Adj. R-squared:                  0.532\n",
      "Method:                 Least Squares   F-statistic:                     17.74\n",
      "Date:                Thu, 03 Mar 2022   Prob (F-statistic):           2.10e-09\n",
      "Time:                        00:07:34   Log-Likelihood:                 89.673\n",
      "No. Observations:                  60   AIC:                            -169.3\n",
      "Df Residuals:                      55   BIC:                            -158.9\n",
      "Df Model:                           4                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      0.0054      0.008      0.676      0.502      -0.011       0.021\n",
      "mkt            1.4461      0.188      7.709      0.000       1.070       1.822\n",
      "smb           -0.4336      0.340     -1.276      0.207      -1.115       0.247\n",
      "hml           -0.7914      0.274     -2.888      0.006      -1.341      -0.242\n",
      "mom            0.2220      0.269      0.826      0.412      -0.316       0.760\n",
      "==============================================================================\n",
      "Omnibus:                        0.390   Durbin-Watson:                   2.032\n",
      "Prob(Omnibus):                  0.823   Jarque-Bera (JB):                0.276\n",
      "Skew:                           0.163   Prob(JB):                        0.871\n",
      "Kurtosis:                       2.933   Cond. No.                         50.8\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "four_factor_model = smf.ols(\n",
    "    formula=\"excess_rtn ~ mkt + smb + hml + mom\", \n",
    "    data=factor_4_df\n",
    ").fit()\n",
    "\n",
    "print(four_factor_model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "9. Estimate the five-factor model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-19T20:31:18.527101Z",
     "start_time": "2020-01-19T20:31:18.495505Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:             excess_rtn   R-squared:                       0.612\n",
      "Model:                            OLS   Adj. R-squared:                  0.576\n",
      "Method:                 Least Squares   F-statistic:                     17.01\n",
      "Date:                Thu, 03 Mar 2022   Prob (F-statistic):           4.54e-10\n",
      "Time:                        00:07:35   Log-Likelihood:                 93.191\n",
      "No. Observations:                  60   AIC:                            -174.4\n",
      "Df Residuals:                      54   BIC:                            -161.8\n",
      "Df Model:                           5                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      0.0059      0.008      0.772      0.444      -0.009       0.021\n",
      "mkt            1.5117      0.193      7.851      0.000       1.126       1.898\n",
      "smb           -0.9411      0.335     -2.807      0.007      -1.613      -0.269\n",
      "hml           -0.5433      0.281     -1.936      0.058      -1.106       0.019\n",
      "rmw           -1.1628      0.513     -2.266      0.027      -2.191      -0.134\n",
      "cma           -0.5153      0.509     -1.012      0.316      -1.536       0.505\n",
      "==============================================================================\n",
      "Omnibus:                        0.073   Durbin-Watson:                   2.074\n",
      "Prob(Omnibus):                  0.964   Jarque-Bera (JB):                0.181\n",
      "Skew:                          -0.077   Prob(JB):                        0.913\n",
      "Kurtosis:                       2.779   Cond. No.                         79.4\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "five_factor_model = smf.ols(\n",
    "    formula=\"excess_rtn ~ mkt + smb + hml + rmw + cma\", \n",
    "    data=factor_5_df\n",
    ").fit()\n",
    "\n",
    "print(five_factor_model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8.5 Estimating cross-sectional factor models using the Fama-MacBeth regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to do it..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Import the libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pandas_datareader.data as web\n",
    "from linearmodels.asset_pricing import LinearFactorModel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Specify the time horizon:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "START_DATE = \"2010\"\n",
    "END_DATE = \"2020-12\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Download and adjust the risk factors from prof. French's website:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mkt-RF</th>\n",
       "      <th>SMB</th>\n",
       "      <th>HML</th>\n",
       "      <th>RMW</th>\n",
       "      <th>CMA</th>\n",
       "      <th>RF</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01</th>\n",
       "      <td>-0.0336</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0043</td>\n",
       "      <td>-0.0123</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02</th>\n",
       "      <td>0.0340</td>\n",
       "      <td>0.0151</td>\n",
       "      <td>0.0322</td>\n",
       "      <td>-0.0028</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-03</th>\n",
       "      <td>0.0631</td>\n",
       "      <td>0.0185</td>\n",
       "      <td>0.0221</td>\n",
       "      <td>-0.0063</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04</th>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0498</td>\n",
       "      <td>0.0289</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0174</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-05</th>\n",
       "      <td>-0.0789</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>-0.0244</td>\n",
       "      <td>0.0127</td>\n",
       "      <td>-0.0023</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Mkt-RF     SMB     HML     RMW     CMA      RF\n",
       "Date                                                   \n",
       "2010-01 -0.0336  0.0035  0.0043 -0.0123  0.0044  0.0000\n",
       "2010-02  0.0340  0.0151  0.0322 -0.0028  0.0140  0.0000\n",
       "2010-03  0.0631  0.0185  0.0221 -0.0063  0.0167  0.0001\n",
       "2010-04  0.0200  0.0498  0.0289  0.0070  0.0174  0.0001\n",
       "2010-05 -0.0789  0.0004 -0.0244  0.0127 -0.0023  0.0001"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factor_5_df = (\n",
    "    web.DataReader(\"F-F_Research_Data_5_Factors_2x3\", \n",
    "                   \"famafrench\", \n",
    "                   start=START_DATE, \n",
    "                   end=END_DATE)[0]\n",
    "    .div(100)\n",
    ")\n",
    "factor_5_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Download and adjust the returns of 12 Industry Portfolios from prof. French's website:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NoDur</th>\n",
       "      <th>Durbl</th>\n",
       "      <th>Manuf</th>\n",
       "      <th>Enrgy</th>\n",
       "      <th>Chems</th>\n",
       "      <th>BusEq</th>\n",
       "      <th>Telcm</th>\n",
       "      <th>Utils</th>\n",
       "      <th>Shops</th>\n",
       "      <th>Hlth</th>\n",
       "      <th>Money</th>\n",
       "      <th>Other</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01</th>\n",
       "      <td>-0.0233</td>\n",
       "      <td>-0.0094</td>\n",
       "      <td>-0.0436</td>\n",
       "      <td>-0.0489</td>\n",
       "      <td>-0.0109</td>\n",
       "      <td>-0.0793</td>\n",
       "      <td>-0.0670</td>\n",
       "      <td>-0.0449</td>\n",
       "      <td>-0.0185</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0107</td>\n",
       "      <td>-0.0256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02</th>\n",
       "      <td>0.0272</td>\n",
       "      <td>0.0738</td>\n",
       "      <td>0.0583</td>\n",
       "      <td>0.0256</td>\n",
       "      <td>0.0413</td>\n",
       "      <td>0.0481</td>\n",
       "      <td>0.0285</td>\n",
       "      <td>-0.0041</td>\n",
       "      <td>0.0429</td>\n",
       "      <td>0.0038</td>\n",
       "      <td>0.0270</td>\n",
       "      <td>0.0465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-03</th>\n",
       "      <td>0.0597</td>\n",
       "      <td>0.0948</td>\n",
       "      <td>0.0779</td>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.0410</td>\n",
       "      <td>0.0666</td>\n",
       "      <td>0.0759</td>\n",
       "      <td>0.0312</td>\n",
       "      <td>0.0623</td>\n",
       "      <td>0.0360</td>\n",
       "      <td>0.0816</td>\n",
       "      <td>0.0886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04</th>\n",
       "      <td>-0.0094</td>\n",
       "      <td>0.0748</td>\n",
       "      <td>0.0422</td>\n",
       "      <td>0.0404</td>\n",
       "      <td>0.0127</td>\n",
       "      <td>0.0220</td>\n",
       "      <td>0.0358</td>\n",
       "      <td>0.0284</td>\n",
       "      <td>0.0255</td>\n",
       "      <td>-0.0223</td>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-05</th>\n",
       "      <td>-0.0569</td>\n",
       "      <td>-0.0900</td>\n",
       "      <td>-0.0920</td>\n",
       "      <td>-0.1023</td>\n",
       "      <td>-0.0677</td>\n",
       "      <td>-0.0769</td>\n",
       "      <td>-0.0582</td>\n",
       "      <td>-0.0630</td>\n",
       "      <td>-0.0535</td>\n",
       "      <td>-0.0802</td>\n",
       "      <td>-0.0922</td>\n",
       "      <td>-0.0822</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          NoDur   Durbl   Manuf   Enrgy   Chems   BusEq   Telcm   Utils  \\\n",
       "Date                                                                      \n",
       "2010-01 -0.0233 -0.0094 -0.0436 -0.0489 -0.0109 -0.0793 -0.0670 -0.0449   \n",
       "2010-02  0.0272  0.0738  0.0583  0.0256  0.0413  0.0481  0.0285 -0.0041   \n",
       "2010-03  0.0597  0.0948  0.0779  0.0323  0.0410  0.0666  0.0759  0.0312   \n",
       "2010-04 -0.0094  0.0748  0.0422  0.0404  0.0127  0.0220  0.0358  0.0284   \n",
       "2010-05 -0.0569 -0.0900 -0.0920 -0.1023 -0.0677 -0.0769 -0.0582 -0.0630   \n",
       "\n",
       "          Shops   Hlth    Money   Other  \n",
       "Date                                     \n",
       "2010-01 -0.0185 -0.0001 -0.0107 -0.0256  \n",
       "2010-02  0.0429  0.0038  0.0270  0.0465  \n",
       "2010-03  0.0623  0.0360  0.0816  0.0886  \n",
       "2010-04  0.0255 -0.0223  0.0092  0.0430  \n",
       "2010-05 -0.0535 -0.0802 -0.0922 -0.0822  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio_df = (\n",
    "    web.DataReader(\"12_Industry_Portfolios\", \n",
    "                   \"famafrench\", \n",
    "                   start=START_DATE, \n",
    "                   end=END_DATE)[0]\n",
    "    .div(100)\n",
    "    .sub(factor_5_df[\"RF\"], axis=0)\n",
    ")\n",
    "portfolio_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. Drop the risk-free rate from the factor data set:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mkt-RF</th>\n",
       "      <th>SMB</th>\n",
       "      <th>HML</th>\n",
       "      <th>RMW</th>\n",
       "      <th>CMA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01</th>\n",
       "      <td>-0.0336</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0043</td>\n",
       "      <td>-0.0123</td>\n",
       "      <td>0.0044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02</th>\n",
       "      <td>0.0340</td>\n",
       "      <td>0.0151</td>\n",
       "      <td>0.0322</td>\n",
       "      <td>-0.0028</td>\n",
       "      <td>0.0140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-03</th>\n",
       "      <td>0.0631</td>\n",
       "      <td>0.0185</td>\n",
       "      <td>0.0221</td>\n",
       "      <td>-0.0063</td>\n",
       "      <td>0.0167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04</th>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0498</td>\n",
       "      <td>0.0289</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-05</th>\n",
       "      <td>-0.0789</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>-0.0244</td>\n",
       "      <td>0.0127</td>\n",
       "      <td>-0.0023</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Mkt-RF     SMB     HML     RMW     CMA\n",
       "Date                                           \n",
       "2010-01 -0.0336  0.0035  0.0043 -0.0123  0.0044\n",
       "2010-02  0.0340  0.0151  0.0322 -0.0028  0.0140\n",
       "2010-03  0.0631  0.0185  0.0221 -0.0063  0.0167\n",
       "2010-04  0.0200  0.0498  0.0289  0.0070  0.0174\n",
       "2010-05 -0.0789  0.0004 -0.0244  0.0127 -0.0023"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factor_5_df = factor_5_df.drop(\"RF\", axis=1)\n",
    "factor_5_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6. Estimate the Fama-MacBeth regression and print the summary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      LinearFactorModel Estimation Summary                      \n",
      "================================================================================\n",
      "No. Test Portfolios:                 12   R-squared:                      0.7906\n",
      "No. Factors:                          5   J-statistic:                    9.9132\n",
      "No. Observations:                   132   P-value                         0.1935\n",
      "Date:                  Thu, Mar 03 2022   Distribution:                  chi2(7)\n",
      "Time:                          00:14:16                                         \n",
      "Cov. Estimator:                  robust                                         \n",
      "                                                                                \n",
      "                            Risk Premia Estimates                             \n",
      "==============================================================================\n",
      "            Parameter  Std. Err.     T-stat    P-value    Lower CI    Upper CI\n",
      "------------------------------------------------------------------------------\n",
      "Mkt-RF         0.0123     0.0038     3.2629     0.0011      0.0049      0.0198\n",
      "SMB           -0.0063     0.0052    -1.2085     0.2269     -0.0165      0.0039\n",
      "HML           -0.0089     0.0032    -2.7764     0.0055     -0.0152     -0.0026\n",
      "RMW           -0.0009     0.0046    -0.1953     0.8451     -0.0099      0.0081\n",
      "CMA           -0.0025     0.0039    -0.6467     0.5178     -0.0100      0.0051\n",
      "==============================================================================\n",
      "\n",
      "Covariance estimator:\n",
      "HeteroskedasticCovariance\n",
      "See full_summary for complete results\n"
     ]
    }
   ],
   "source": [
    "five_factor_model = LinearFactorModel(\n",
    "    portfolios=portfolio_df, \n",
    "    factors=factor_5_df\n",
    ")\n",
    "result = five_factor_model.fit()\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also print the full summary (1 aggregate and 12 individual ones for each portfolio separately)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      LinearFactorModel Estimation Summary                      \n",
      "================================================================================\n",
      "No. Test Portfolios:                 12   R-squared:                      0.7906\n",
      "No. Factors:                          5   J-statistic:                    9.9132\n",
      "No. Observations:                   132   P-value                         0.1935\n",
      "Date:                  Thu, Mar 03 2022   Distribution:                  chi2(7)\n",
      "Time:                          00:14:16                                         \n",
      "Cov. Estimator:                  robust                                         \n",
      "                                                                                \n",
      "                            Risk Premia Estimates                             \n",
      "==============================================================================\n",
      "            Parameter  Std. Err.     T-stat    P-value    Lower CI    Upper CI\n",
      "------------------------------------------------------------------------------\n",
      "Mkt-RF         0.0123     0.0038     3.2629     0.0011      0.0049      0.0198\n",
      "SMB           -0.0063     0.0052    -1.2085     0.2269     -0.0165      0.0039\n",
      "HML           -0.0089     0.0032    -2.7764     0.0055     -0.0152     -0.0026\n",
      "RMW           -0.0009     0.0046    -0.1953     0.8451     -0.0099      0.0081\n",
      "CMA           -0.0025     0.0039    -0.6467     0.5178     -0.0100      0.0051\n",
      "\n",
      "\n",
      "                              NoDur Coefficients                              \n",
      "==============================================================================\n",
      "            Parameter  Std. Err.     T-stat    P-value    Lower CI    Upper CI\n",
      "------------------------------------------------------------------------------\n",
      "alpha         -0.0008     0.0015    -0.5523     1.4192     -0.0038      0.0021\n",
      "Mkt-RF         0.7861     0.0455     17.271     0.0000      0.6969      0.8753\n",
      "SMB           -0.2158     0.0946    -2.2820     1.9775     -0.4012     -0.0305\n",
      "HML           -0.0838     0.1020    -0.8217     1.5888     -0.2838      0.1161\n",
      "RMW            0.4681     0.1211     3.8663     0.0001      0.2308      0.7054\n",
      "CMA            0.3388     0.1498     2.2619     0.0237      0.0452      0.6324\n",
      "\n",
      "\n",
      "                              Durbl Coefficients                              \n",
      "==============================================================================\n",
      "alpha          0.0020     0.0021     0.9666     0.3337     -0.0021      0.0062\n",
      "Mkt-RF         1.5488     0.1479     10.474     0.0000      1.2590      1.8386\n",
      "SMB            0.5808     0.1796     3.2342     0.0012      0.2288      0.9329\n",
      "HML           -0.1684     0.1708    -0.9860     1.6759     -0.5030      0.1663\n",
      "RMW            0.2942     0.4764     0.6176     0.5369     -0.6395      1.2279\n",
      "CMA            0.2994     0.2703     1.1078     0.2679     -0.2303      0.8291\n",
      "\n",
      "\n",
      "                              Manuf Coefficients                              \n",
      "==============================================================================\n",
      "alpha          0.0014     0.0016     0.8404     0.4007     -0.0018      0.0045\n",
      "Mkt-RF         1.0950     0.0481     22.749     0.0000      1.0006      1.1893\n",
      "SMB            0.2910     0.0625     4.6554     0.0000      0.1685      0.4135\n",
      "HML            0.1468     0.0596     2.4640     0.0137      0.0300      0.2636\n",
      "RMW            0.0867     0.1180     0.7346     0.4626     -0.1446      0.3180\n",
      "CMA           -0.0110     0.1186    -0.0926     1.0738     -0.2435      0.2215\n",
      "\n",
      "\n",
      "                              Enrgy Coefficients                              \n",
      "==============================================================================\n",
      "alpha         -0.0037     0.0021    -1.7798     1.9249     -0.0078      0.0004\n",
      "Mkt-RF         1.2480     0.1279     9.7577     0.0000      0.9973      1.4987\n",
      "SMB            0.4873     0.1796     2.7135     0.0067      0.1353      0.8393\n",
      "HML            0.6308     0.1674     3.7677     0.0002      0.3027      0.9589\n",
      "RMW            0.2439     0.3043     0.8012     0.4230     -0.3526      0.8404\n",
      "CMA            0.4045     0.2683     1.5074     0.1317     -0.1214      0.9305\n",
      "\n",
      "\n",
      "                              Chems Coefficients                              \n",
      "==============================================================================\n",
      "alpha         -0.0012     0.0015    -0.8116     1.5830     -0.0040      0.0017\n",
      "Mkt-RF         0.8852     0.0465     19.020     0.0000      0.7940      0.9764\n",
      "SMB           -0.0893     0.0856    -1.0438     1.7034     -0.2570      0.0784\n",
      "HML           -0.0185     0.0561    -0.3298     1.2585     -0.1284      0.0914\n",
      "RMW            0.1720     0.0910     1.8909     0.0586     -0.0063      0.3503\n",
      "CMA            0.2107     0.1048     2.0117     0.0443      0.0054      0.4160\n",
      "\n",
      "\n",
      "                              BusEq Coefficients                              \n",
      "==============================================================================\n",
      "alpha         -0.0022     0.0015    -1.4658     1.8573     -0.0051      0.0007\n",
      "Mkt-RF         1.1169     0.0336     33.235     0.0000      1.0511      1.1828\n",
      "SMB           -0.1798     0.0639    -2.8132     1.9951     -0.3050     -0.0545\n",
      "HML           -0.1429     0.0718    -1.9907     1.9535     -0.2836     -0.0022\n",
      "RMW           -0.0223     0.0970    -0.2299     1.1818     -0.2123      0.1677\n",
      "CMA           -0.5616     0.1099    -5.1080     2.0000     -0.7771     -0.3461\n",
      "\n",
      "\n",
      "                              Telcm Coefficients                              \n",
      "==============================================================================\n",
      "alpha          0.0010     0.0020     0.4845     0.6280     -0.0029      0.0049\n",
      "Mkt-RF         0.8962     0.0484     18.517     0.0000      0.8014      0.9911\n",
      "SMB           -0.0954     0.0906    -1.0526     1.7075     -0.2730      0.0822\n",
      "HML           -0.0862     0.1253    -0.6878     1.5084     -0.3319      0.1595\n",
      "RMW            0.2448     0.1192     2.0532     0.0401      0.0111      0.4784\n",
      "CMA            0.6837     0.2044     3.3455     0.0008      0.2832      1.0843\n",
      "\n",
      "\n",
      "                              Utils Coefficients                              \n",
      "==============================================================================\n",
      "alpha          0.0029     0.0025     1.1826     0.2370     -0.0019      0.0077\n",
      "Mkt-RF         0.4577     0.0770     5.9437     0.0000      0.3067      0.6086\n",
      "SMB           -0.1272     0.1411    -0.9011     1.6325     -0.4037      0.1494\n",
      "HML            0.0769     0.1841     0.4179     0.6760     -0.2839      0.4378\n",
      "RMW            0.3192     0.2109     1.5137     0.1301     -0.0941      0.7325\n",
      "CMA            0.1941     0.2739     0.7088     0.4785     -0.3427      0.7309\n",
      "\n",
      "\n",
      "                              Shops Coefficients                              \n",
      "==============================================================================\n",
      "alpha          0.0007     0.0019     0.4031     0.6869     -0.0029      0.0044\n",
      "Mkt-RF         0.9482     0.0458     20.685     0.0000      0.8583      1.0380\n",
      "SMB            0.0568     0.0775     0.7336     0.4632     -0.0950      0.2086\n",
      "HML           -0.3332     0.0618    -5.3949     2.0000     -0.4543     -0.2122\n",
      "RMW            0.4477     0.1086     4.1221     0.0000      0.2348      0.6606\n",
      "CMA            0.2888     0.1083     2.6673     0.0076      0.0766      0.5010\n",
      "\n",
      "\n",
      "                              Hlth  Coefficients                              \n",
      "==============================================================================\n",
      "alpha         -0.0016     0.0021    -0.7540     1.5492     -0.0056      0.0025\n",
      "Mkt-RF         0.8193     0.0504     16.268     0.0000      0.7205      0.9180\n",
      "SMB            0.0169     0.0949     0.1783     0.8585     -0.1690      0.2028\n",
      "HML           -0.4532     0.0933    -4.8574     2.0000     -0.6361     -0.2703\n",
      "RMW           -0.3409     0.1389    -2.4541     1.9859     -0.6131     -0.0686\n",
      "CMA            0.2833     0.1606     1.7635     0.0778     -0.0316      0.5981\n",
      "\n",
      "\n",
      "                              Money Coefficients                              \n",
      "==============================================================================\n",
      "alpha          0.0024     0.0017     1.4241     0.1544     -0.0009      0.0056\n",
      "Mkt-RF         1.0385     0.0335     30.967     0.0000      0.9728      1.1043\n",
      "SMB           -0.0043     0.0703    -0.0611     1.0487     -0.1422      0.1336\n",
      "HML            0.6226     0.0665     9.3611     0.0000      0.4922      0.7530\n",
      "RMW           -0.5510     0.0815    -6.7618     2.0000     -0.7107     -0.3913\n",
      "CMA           -0.3396     0.1091    -3.1131     1.9981     -0.5534     -0.1258\n",
      "\n",
      "\n",
      "                              Other Coefficients                              \n",
      "==============================================================================\n",
      "alpha       3.703e-05     0.0014     0.0271     0.9784     -0.0026      0.0027\n",
      "Mkt-RF         1.0369     0.0409     25.359     0.0000      0.9567      1.1170\n",
      "SMB            0.0824     0.0548     1.5024     0.1330     -0.0251      0.1898\n",
      "HML            0.0969     0.0592     1.6361     0.1018     -0.0192      0.2130\n",
      "RMW            0.1131     0.1051     1.0766     0.2817     -0.0928      0.3191\n",
      "CMA            0.2255     0.0947     2.3800     0.0173      0.0398      0.4112\n",
      "==============================================================================\n",
      "\n",
      "Covariance estimator:\n",
      "HeteroskedasticCovariance\n",
      "See full_summary for complete results\n"
     ]
    }
   ],
   "source": [
    "print(result.full_summary)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### There's more"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Import the libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.api import OLS, add_constant"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. First step - estimate the factor loadings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "factor_loadings = []\n",
    "for portfolio in portfolio_df:\n",
    "    reg_1 = OLS(\n",
    "        endog=portfolio_df.loc[:, portfolio], \n",
    "        exog=add_constant(factor_5_df)\n",
    "    ).fit()\n",
    "    factor_loadings.append(reg_1.params.drop(\"const\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Store the factor loadings in a DataFrame:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mkt-RF</th>\n",
       "      <th>SMB</th>\n",
       "      <th>HML</th>\n",
       "      <th>RMW</th>\n",
       "      <th>CMA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NoDur</th>\n",
       "      <td>0.786087</td>\n",
       "      <td>-0.215818</td>\n",
       "      <td>-0.083847</td>\n",
       "      <td>0.468129</td>\n",
       "      <td>0.338823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Durbl</th>\n",
       "      <td>1.548809</td>\n",
       "      <td>0.580849</td>\n",
       "      <td>-0.168357</td>\n",
       "      <td>0.294196</td>\n",
       "      <td>0.299400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manuf</th>\n",
       "      <td>1.094951</td>\n",
       "      <td>0.291003</td>\n",
       "      <td>0.146831</td>\n",
       "      <td>0.086695</td>\n",
       "      <td>-0.010987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enrgy</th>\n",
       "      <td>1.248025</td>\n",
       "      <td>0.487285</td>\n",
       "      <td>0.630805</td>\n",
       "      <td>0.243854</td>\n",
       "      <td>0.404512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chems</th>\n",
       "      <td>0.885184</td>\n",
       "      <td>-0.089296</td>\n",
       "      <td>-0.018501</td>\n",
       "      <td>0.171997</td>\n",
       "      <td>0.210732</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Mkt-RF       SMB       HML       RMW       CMA\n",
       "NoDur  0.786087 -0.215818 -0.083847  0.468129  0.338823\n",
       "Durbl  1.548809  0.580849 -0.168357  0.294196  0.299400\n",
       "Manuf  1.094951  0.291003  0.146831  0.086695 -0.010987\n",
       "Enrgy  1.248025  0.487285  0.630805  0.243854  0.404512\n",
       "Chems  0.885184 -0.089296 -0.018501  0.171997  0.210732"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factor_load_df = pd.DataFrame(\n",
    "    factor_loadings, \n",
    "    columns=factor_5_df.columns, \n",
    "    index=portfolio_df.columns\n",
    ")\n",
    "factor_load_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Second step - estimate the risk premia:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "risk_premia = []\n",
    "for period in portfolio_df.index:\n",
    "    reg_2 = OLS(\n",
    "        endog=portfolio_df.loc[period, factor_load_df.index], \n",
    "        exog=factor_load_df\n",
    "    ).fit()\n",
    "    risk_premia.append(reg_2.params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. Store the risk premia in a DataFrame:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mkt-RF</th>\n",
       "      <th>SMB</th>\n",
       "      <th>HML</th>\n",
       "      <th>RMW</th>\n",
       "      <th>CMA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01</th>\n",
       "      <td>-0.032631</td>\n",
       "      <td>0.051998</td>\n",
       "      <td>-0.023749</td>\n",
       "      <td>-0.039525</td>\n",
       "      <td>0.015071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02</th>\n",
       "      <td>0.036662</td>\n",
       "      <td>0.020982</td>\n",
       "      <td>-0.014351</td>\n",
       "      <td>0.027181</td>\n",
       "      <td>-0.029331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-03</th>\n",
       "      <td>0.065954</td>\n",
       "      <td>-0.031731</td>\n",
       "      <td>-0.003074</td>\n",
       "      <td>-0.001531</td>\n",
       "      <td>-0.001160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04</th>\n",
       "      <td>0.019455</td>\n",
       "      <td>0.048860</td>\n",
       "      <td>0.009688</td>\n",
       "      <td>0.040766</td>\n",
       "      <td>-0.014576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-05</th>\n",
       "      <td>-0.076882</td>\n",
       "      <td>0.024591</td>\n",
       "      <td>-0.021421</td>\n",
       "      <td>0.021403</td>\n",
       "      <td>-0.014296</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Mkt-RF       SMB       HML       RMW       CMA\n",
       "Date                                                     \n",
       "2010-01 -0.032631  0.051998 -0.023749 -0.039525  0.015071\n",
       "2010-02  0.036662  0.020982 -0.014351  0.027181 -0.029331\n",
       "2010-03  0.065954 -0.031731 -0.003074 -0.001531 -0.001160\n",
       "2010-04  0.019455  0.048860  0.009688  0.040766 -0.014576\n",
       "2010-05 -0.076882  0.024591 -0.021421  0.021403 -0.014296"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "risk_premia_df = pd.DataFrame(\n",
    "    risk_premia, \n",
    "    index=portfolio_df.index,\n",
    "    columns=factor_load_df.columns.tolist())\n",
    "risk_premia_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6. Calculate the average risk premia:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mkt-RF    0.012339\n",
       "SMB      -0.006277\n",
       "HML      -0.008939\n",
       "RMW      -0.000895\n",
       "CMA      -0.002490\n",
       "dtype: float64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "risk_premia_df.mean()"
   ]
  }
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